Ever since Facebook expanded access to its Messenger service in April 2016, giving businesses the ability to reach customers through APIs, “Chatbot” has become the buzzword in developer communities across the globe. Here is a short piece on the essentials for investing resources in chatbots that may be helpful to startups and established businesses alike.
Image : shutterstock
What's hot about it?
There is a certain ‘wow factor’ when someone books a cab or orders a bouquet of flowers simply through a conversation. It’s a never-seen-before phenomenon where computing intelligence uses natural human language to deliver simplified consumer experiences.
Chatbots have the advantage of enabling users to access business services while on chat platforms like Facebook Messenger and Telegram. What this could mean is that the search and discovery function may shift away from Google and apps, to chat platforms because of their pure simplicity and convenience. This development truly has the potential to become the ‘next big thing’ when businesses invest sufficiently in this technology and when more chat platforms like Whatsapp join the party. Hence, the hype around the announcements of Facebook and Microsoft in the last few weeks is justified.
In India, we have already seen a few bots like Niki and MagicX trying to make their presence felt in the travel and grocery categories in India. There are certainly more developments expected out of them and a few other players like Haptik (funded by Times Internet), which are trying to solve more ‘use cases’ for assisting users on chat platforms through human-supported bots.
One can foresee two sets of chatbots emerging in the next few months: (1) stand alone bots that solve for conversations and (2) bots that are platform extensions of businesses like Flipkart and Amazon. The latter scenario notably creates opportunities for developers to offer bots as a service or customised product for businesses that cannot afford to develop them in-house. This could be especially useful for functions like customer support that use scripted, template-based human conversations.
Why should a business invest in a bot?
In the West, human-supported bots, developed by companies such as Interactions, started surfacing in the last decade or so, particularly in the customer support domain in order to reduce manpower requirements and thus costs. The adoption of such technology, to reduce customer support costs, will become increasingly important in the Indian market in the coming years.
As key chat apps become more accessible to businesses, they will need to prepare to engage their customers on chat platforms across various use cases, including (i) service and product discovery, (ii) ordering, and (iii) customer support. As supply and demand volumes increase, though it is still early to predict, we may soon come across ecommerce companies talking about the growing pie of the conversational commerce market. Similarly, we might hear of content-based online businesses talking about their content consumption on chat platforms. There are teams like Nanorep that are already in the market offering bots as a service to ecommerce firms.
The importance of Artificial Intelligence (AI)
From Apple's Siri days to the Cortana and Skype announcements by Microsoft in March 2016, the ability to collect data from the relevant source and communicate this information to the user via a conversation has been the main talking point of the well-known developers. It often seems that conversations (chatbots) are something that standalone NLP technology (natural language processing) can deliver; however, in reality, it depends on the domain and expertise that the bot is being used for. In other words, the AI is fundamentally about your business domain, expertise, and consumer use cases, which are not very different from what your app and website are about. It is just that, additionally, the bot can interact with your consumers and have conversations playing the role of a sales rep, domain expert or customer support agent – without any human support.
What problem is your startup solving?
While startups in this space are rushing to get a head-start, it is important to solve specific consumer problems. Bots that are banking purely on the conversation format, contextual understanding, natural language understanding (NLU), and are smart at calling other services, would eventually have competition from global giants like Viv, Microsoft, Google and Facebook. In addition, large online businesses could soon follow Amazon, which is estimated to have sold three million units of its voice recognition technology, Ecko, thus making a strong case for expanding into the conversational commerce space.
Building of a chatbot
While the actual NLP use cases were earlier regarded as complex and demanding advanced data sciences capabilities, the key problem now looks simpler than ever before with the emergence of players like wit.ai (acquired by Facebook), which are trying to come up with APIs that offer simplified solutions for setting up conversations. To interpret consumer queries, convert them to specific topics, run them through the conversation and knowledge engines to shoot back replies, the skill-sets required are far simpler now and the technology needed is freely accessible.
The need to feed up the knowledge engine with domain intelligence is where the business needs to focus on, if the bot is to be an additional platform to the core business alongside the web and apps. However, for startups building their models purely on chat platforms, there could possibly be some merit in having their own libraries in components like knowledge engines, as they scale in order to reduce dependency on third-party tools.
Chatbot startups that are not extensions of websites and apps can essentially adopt any of the three approaches for training the bot:
- Build a smart bot that learns from its user interactions – Consumers often expect your bot to be near-perfect in their first interaction. Therefore, it is risky to assume that your bot can afford to learn from its user interactions. Rather, it needs to be fully prepared before interacting with its users.
- Have humans supporting the bot until it gets trained sufficiently – The large players who are dealing with open-ended use cases, including Facebook's Messenger, are reportedly taking this approach. While this brings in control, it can demand heavy investments in the initial years and, also, runs the risk of ending up as a semi-human application.
- Train your bot sufficiently with content and structured data – While eventful applications in AI such as IBM Watson and Google's AlphaGo were largely trained with a mix of structured and unstructured content, as well as massive data from human actions and algorithms built on top of it, it is very expensive and time consuming. And although this is arguably the best approach for building complex and scalable bots – ones that are capable of dealing with qualitative and judgement-based use cases – it has yet to be seen how the funding ecosystem in India will embrace the idea, in terms of patience and risk appetite.
With the biggies investing so heavily in conversational canvases and driving traffic and engagement on chat platforms, it is almost certain that businesses will eventually have to compete fiercely through chatbots, just as they are now doing on web and mobile platforms. It will also be the time when the Indian startup ecosystem would build capabilities to grab a piece of the chatbot pie, be it in the area of (i) search and discovery, (ii) expertise, assistance and conversation-dependent business cases, and (iii) reducing template-based human interactions.
Google I/O developer conference, which just took place, is a much-anticipated annual event in the chatbot context. Adding to the recent excitement about chatbots, Google’s Project Chirp – officially now known as Google Home – is reportedly Google’s reply and competition to Amazon's Ecko and is expected to be unveiled later this year. Exciting times ahead!
The article is co-authored by Mr. K.V. Ravisekhar. Ravi is an entrepreneur and startup advisor and previously led marketing tech, digital marketing and CRM at ebay India.
(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)
